Meaning in life,connectedness,academic self-efficacy,and personal self-efficacy: A winning combination

Abstract

Limited research has been conducted so far to explore how meaning in life can promote key academic and psychological benefits in a school context. The research reported here aimed to address this issue by assessing how meaning in life is associated with dimensions of connectedness, academic self-efficacy (Study 1) and personal self-efficacy (Study 2). Participants were two samples of Hong Kong secondary school students. Study 1 revealed that meaning in life was associated with a higher level of connectedness to parents, school, peers, and teachers, and academic self-efficacy (study skills, time management, critical and creative thinking, and involvement in learning). Most connectedness dimensions were linked to lower academic self-efficacy, apart from connectedness to school. Study 2 showed that meaning in life was linked to higher levels of connectedness and personal self-efficacy dimensions (positive self-concept, problem-solving, self-management, and self-reflection). Apart from connectedness to school, other connectedness dimensions were associated with lower personal self-efficacy. Across studies, meaning in life had indirect effects on both self-efficacy through the mediating influence of connectedness. Theoretical and practical implications are discussed.

Keywords

adolescents connectedness meaning in life secondary school students self-efficacy student outcomes

Introduction

Humans are fundamentally driven to achieve a meaningful life, and to some extent meaning in life serves as an essential marker of psychological health (Lent, 2004; Ryff, 1989; Steger et al., 2006). Previous studies have consistently shown that meaning in life is associated with optimal positive psychological outcomes such as well-being (Brassai et al., 2015; Datu & Mateo, 2015), generalized self-efficacy (Lightsey et al., 2014), and career adaptability (Yuen & Yau, 2015). Recognizing the growing interest in this research area, Steger et al. (2006) have proposed a theoretical model which regards meaning in life as “the sense made of, and significance felt regarding, the nature of one’s being and existence” (p. 81). An existentialist perspective has argued that meaningful living is essential for self-growth and psychological well-being (Frankl, 1959, 1984; Kenyon, 2000; Ryff & Singer, 1998).

A review of the pertinent literature indicates that meaning in life is often related to generalized self-efficacy in various population samples such as undergraduate students (Lightsey et al., 2014) and older women (Jafary et al., 2011). Meaning in life is also thought to predict self-efficacy in career decision making (Sari, 2019). However, little is known about how meaning in life influences specific domains of self-efficacy (e.g., academic and personal). It is also evident that past research has largely focused on adult samples, and the influence of meaning in life has been relatively ignored in a secondary school context. In particular, studies to date have not explored in sufficient depth the mechanisms which could explain why meaning in life helps to foster positive academic outcomes for students. A search revealed only the studies of Kiang and Witkow (2015) and Brassai et al. (2015) that examined meaning in life and positive outcomes in high school students.

With these points in mind, the study reported here aimed to assess the extent to which presence of meaning in life may be related to different domains of academic self-efficacy, personal self-efficacy, and social connectedness. Data were collected from two samples of secondary school students in Hong Kong. The possible mediating effect of connectedness on any links between meaning in life and self-efficacy domains was also examined.

Meaning in life and psychological outcomes

The extant literature supports a view that meaning in life is an important variable affecting a person’s psychological well-being and quality of life. Human beings experience a need to search for meaning in their lives, to motivate them and give them a sense of purpose (Frankl, 1959; Steger et al., 2006; Yuen et al., 2017). Steger et al. (2006) assert that meaning in life exists in two forms, namely presence of meaning in life (POM)―which refers to a state where an individual has already recognized his or her life is meaningful―and search for meaning in life (SFM) which pertains to the state of still seeking meaning in one’s life.

Among adults, POM has been more strongly associated than SFM with variables that represent positive psychological functioning. Research has indicated that POM is related to outcomes like life satisfaction (Datu & Mateo, 2015; Steger et al., 2006), positive emotions (Datu, 2016), positive self-evaluations (Steger et al., 2006), healthy eating and physical activities (Brassai et al., 2012, 2015), subjective happiness (Vela et al., 2015), and psychological well-being (Krok, 2015). In addition, POM has been associated with lower levels of depression (Park & Jeong, 2016), and state anxiety (Miller & Rottinghaus, 2014). Past studies have also demonstrated that meaning in life is linked to performance and work-related outcomes such as greater motivation (Allan et al., 2016), career decision making (Miller & Rottinghaus, 2014), career adaptability (Yuen & Yau, 2015), and generalized self-efficacy (Lightsey et al., 2014).

In contrast, investigations have shown that SFM has weaker correlations with positive outcomes. It was not associated with positive emotions, life satisfaction, subjective happiness, positive religious coping, and psychological well-being (Krok, 2015; Steger et al., 2006); and SFM was negatively linked with goal-dependent hope (Vela et al., 2014), self-esteem (Kiang & Witkow, 2015) and subjective happiness (Boyraz et al., 2013; Vela et al., 2015). A strong but unsuccessful search for meaning has been associated with greater depression, fear of dying, and negative emotions (Kiang & Witkow, 2015; Steger et al., 2008).

Self-efficacy is an individual’s beliefs concerning his or her own competence in a particular activity or endeavor, and to achieve personal goals (Bandura, 1997). In secondary schools, academic self-efficacy and personal self-efficacy exert strong influences on adolescents’ academic functioning and well-being (Bandura et al., 1996). Academic self-efficacy refers to an individual’s perception of their own capability in using effective study strategies, time management, problem solving, and flexible thinking approaches in the context of academic and extra-curricular tasks (Yuen et al., 2006). Personal self-efficacy refers to an individual’s belief in their own strengths and capabilities in self-regulation, resilience, and the capacity to reflect upon and (where necessary) modify one’s own goals and actions (Yuen et al., 2006).

Given that past empirical studies have suggested that POM plays a more influential role than SFM in enhancing positive student outcomes, the study reported here concentrated on exploring the influence of meaning in life on academic self-efficacy and personal self-efficacy. Previous research has highlighted the advantages of using domain-specific measures of self-efficacy rather than looking only at ‘general’ self-efficacy (Bandura, 1997; Bong, 2002).

The research rationale

The design of this two-part study was guided to some extent by individual psychology and logotherapy (Adler, 1931; Frankl, 1959). These influences led to formulation of hypotheses that suggest a possible meditating effect of connectedness on associations between meaning in life and self-efficacy among adolescents in secondary schools. Adolescents develop their sense of ‘self’ by engaging in the social contexts of family, friendships and school; and feelings of connectedness and meaning in life usually emerge from these experiences (Adler, 1931; Yuen et al., 2012). Through engagement and connectedness to parents, peers and teachers, adolescents develop their self-efficacy in various domains of life (Bandura, 1997; Yuen et al., 2010).

It could be posited that the psychological benefits that accrue from an individual’s strong perception of meaning in life may simultaneously cultivate and strengthen their academic self-efficacy and personal self-efficacy. Indeed, it is logical to argue that meaning in life may have implications for development of self-efficacy in specific domains (e.g., academic performance and life skills). However, in a school setting there are other influences that have an impact on how a student feels, is confident, and is motivated to learn. One variable that has been shown in previous studies to have a positive influence is connectedness (Stavrova & Luhmann, 2016; Yuen, 2011), and this variable may serve as a mechanism that can explain why meaning in life may boost academic and personal self-efficacy. Connectedness may have a mediating effect on the link between meaning in life and self-efficacy (Yuen et al., 2015).

Connectedness—in particular school connectedness—refers to the extent to which students perceive that they are accepted and valued as members of their school community (that they ‘belong’) and are supported by significant others in academic-related tasks (Catalano et al., 2004; Goodenow, 1993). Previous studies have shown that school connectedness is substantially associated with positive academic and psychological well-being outcomes (Goodenow & Grady, 1993; Lonczak et al., 2002; Resnick et al., 1997). It is reasonable to propose that meaning in life can boost students’ sense of school connectedness (and vice versa) for at least three reasons. First, previous research has demonstrated that individuals with stronger meaning in life are likely to be perceived as socially attractive (Steger, Kashdan, et al., 2008; Stillman et al., 2009; 2011). Second, studies have shown that meaning in life may enhance individuals’ inclination to invest effort in establishing harmonious relationships (Steger et al., 2008). Third, the extant literature suggests that meaning in life is related to possessing a higher sense of connectedness (Stavrova & Luhmann, 2016; Steger & Kashdan, 2013; Yuen & Yau, 2015).

With these points in mind, the studies reported here aimed to assess the extent to which presence of meaning in life may be related to different domains of academic self-efficacy, personal self-efficacy, and connectedness (Figure 1

Figure 1.

The associations among meaning in life, connectedness and self-efficacy.

). Data were collected from two samples of secondary school students in Hong Kong. The possible mediating effect of connectedness on any links between meaning in life and self-efficacy domains was also examined. Specifically, the two studies reported here assessed the extent to which presence of meaning in life (POM) was associated with connectedness and with two important domains of self-efficacy in secondary school students in Hong Kong.

Study 1: Meaning in life, connectedness, and academic self-efficacy

The main objective of Study 1 was to examine the association of meaning in life with domains of connectedness and academic self-efficacy. The indirect effects of meaning in life on academic self-efficacy were also investigated through the intermediate variable of students’ connectedness to parents, schools, peers, and teachers. The following hypotheses were tested:

Hypothesis 1: Meaning in life would be positively associated with all dimensions of connectedness (to parents, peers, teachers, and school).

Hypothesis 2: Connectedness would be positively related to domains of academic self-efficacy (study skills, time management, critical and creative thinking, and investment in learning).

Hypothesis 3: Meaning in life would have indirect effects on academic self-efficacy dimensions via the mediating role of connectedness.

Method

The first author applied to the Human Research Ethics Committee of the university to implement data collection activities in 100 randomly selected secondary schools in different regions of Hong Kong. After approval was obtained, the first author communicated with the schools, and 79 agreed to participate. Then consent forms were distributed, and the survey was administered to the participants in groups by their class teachers during the home room periods. All materials were in Chinese. The response rate was 91%.

Participants and procedures

In Study 1, the sample comprised 4,336 Hong Kong secondary school students from school years Grade 7 to Grade 9. The ages of the students ranged from 11 to 18 (M = 13.84, SD = 1.33), 2,199 boys: 2,108 girls. 3373 students (77.80%) were born in Hong Kong. Data collected on the educational level of participants’ fathers and mothers revealed that 12.40% and 12.50% respectively had only primary education or no education, 19.60% and 20.10% respectively had middle school education, 38% and 41.80% had high school education; and 23.90% and 20.40% respectively had some college education.

Measures

Meaning in life

Five items in the ‘presence of meaning’ section of the Chinese version of the Meaning in Life Scale (Steger et al., 2006) were used to measure perceived meaning in life (e.g., “My life has a clear sense of purpose.” Items were marked on a 7-point Likert-type scale (1 = absolutely untrue; 7 = absolutely true). Cronbach’s Alpha reliability coefficient for the scale was .82. Result of confirmatory factor analyses (CFA) showed that this scale had a good fit: χ² = 113.08, df = 5, p <. 001, CFI = .99, TLI = .98, SRMR = .046, and RMSEA = .071 (.060, .082). All items significantly loaded on higher order meaning latent construct at p < .001.

Connectedness

The 24-item Chinese version of the Hemingway Measure of Adolescent Connectedness – Short Form (Yuen et al., 2010) was used to measure students’ perceived connectedness to parents, schools, peers, and teachers (e.g., “My family always has fun together”, “I like working with my classmates”, “I care what my teachers think of me”). Items were rated on a 5-point Likert-type scale (1 = not at all; 5 = very true). Cronbach’s alpha coefficients of the social connectedness dimensions were: α_parents = .79, α _school = .72, α_peers = .68, and α_teachers = .74. CFA demonstrated that a four-factor model of connectedness underpinned by parents, peers, teachers, and school connectedness dimensions had poor fit: χ² = 6247.06, df = 246, p <. 001, CFI = .84, TLI = .82, SRMR = .06, and RMSEA = .075 (.073, .077). However, as some pairs of indicators’ error terms exhibited high modification indices, these error terms were correlated which resulted in a better fitting model, χ² = 3198.81, df = 217, p <. 001, CFI = .92, TLI = .90, SRMR = .045, and RMSEA = .056 (.055, .058). All items significantly loaded on higher order meaning latent construct at p < .001.

Academic self-efficacy

The 24 items in the academic self-efficacy scale of the Life Skills Development Inventories (Yuen et al., 2006) were used to measure the domains of academic self-efficacy of the participants (e.g., study skills “I can apply important study skills such as note-taking, summarizing, memorizing, using reference materials”; time management “I can design my own study timetable, and act accordingly”; critical and creative thinking “I am able to reflect upon the possible ways of tackling school tasks”; investment in learning “I can establish harmonious working relationship with classmates”). Items were marked on a 6-point Likert-type scale (1 = extremely lacking in confidence; 6 = extremely confident). Cronbach’s alpha reliability coefficients of the academic self-efficacy domains were: α_{study skills} = .81, α _{time management} = .88, α_{critical and creative thinking} = .84, and α_{investment in learning} = .80. CFA with a four-factor model of academic self-efficacy indicated that the model had poor fit: χ² = 6538.37, df = 246, p <. 001, CFI = .88, TLI = .86, SRMR = .052, and RMSEA = .077 (.075, .078). However, revising the original measurement model based on modification indices resulted in better fit: χ² = 4177.08, df = 238, p <. 001, CFI = .92, TLI = .91, SRMR = .044, and RMSEA = .062 (.060, .063).

Results and discussion

Preliminary analysis showed that 0.8% of the responses were missing per item, and Little’s MCAR test revealed that such responses were not missing completely at random. Hence, expectation-maximization (EM) imputation approach was used to supply the missing values. Little (1988) has noted that in such cases the use of EM algorithm is acceptable.

Findings of correlation analyses corroborated the theoretical conjecture as meaning in life was positively correlated with all domains of social connectedness (parents, school, peers, and teachers) and academic self-efficacy (study skills, time management, critical and creative thinking, and investment in learning). Dimensions of connectedness were also positively associated with academic self-efficacy (Table 1).

Table 1.

Descriptive statistics and correlational coefficients among the variables in Study 1.

Variable	r									α	M	SD
	1	2	3	4	5	6	7	8	9
1. Meaning in life	–									.82	23.02	5.70
2. Connectedness to parents	.24**	–								.79	3.50	.67
3. Connectedness to school	.32**	.48**	–							.72	3.41	.58
4. Connectedness to peers	.25**	.38**	.42**	–						.68	2.99	.50
5. Connectedness to teachers	.34**	.41**	.62**	.42**	–					.74	3.44	.62
6. Study skills	.36**	.35**	.54**	.35**	.41**	–				.81	4.07	.77
7. Time management	.29**	.37**	.50**	.33**	.32**	.74**	–			.88	4.00	.86
8. Critical and creative thinking	.42**	.34**	.50**	.36**	.37**	.79**	.74**	–		.84	4.24	.76
9. Investment in learning	.38**	.41**	.61**	.51**	.56**	.71**	.63**	.71**	–	.80	4.42	.75

Note: **p < .001.

Table 2.

Unstandardized regression weights of the regression analyses in Study 1.

Paths	B	SE	t
Meaning in Life predicting mediators
Meaning in life → connectedness to parents	.21***	.01	16.14
Meaning in life → connectedness to school	.52***	.02	23.43
Meaning in life → connectedness to peers	.21***	.01	15.02
Meaning in life → connectedness to teachers	.39***	.02	16.50
Mediators predicting outcomes
Connectedness to parents → study skills	−.54***	.13	−4.23
Connectedness to school → study skills	2.97***	.28	10.57
Connectedness to peers → study skills	−.23***	.38	−6.31
Connectedness to teachers → study skills	−.44***	.08	−5.43
Connectedness to parents → time management	−.52***	.16	−3.27
Connectedness to school → time management	3.78***	.35	10.74
Connectedness to peers → time management	−3.19***	.48	−6.67
Connectedness to teachers → time management	−.85***	.10	−8.18
Connectedness to parents → critical and creative thinking	−.50***	.13	−4.01
Connectedness to school → critical and creative thinking	2.89***	.27	10.61
Connectedness to peers → critical and creative thinking	−2.21***	.37	−6.03
Connectedness to teachers → critical and creative thinking	−.51***	.08	−6.36
Connectedness to parents → investment in learning	−.22**	.07	−3.05
Connectedness to school → investment in learning	1.44***	.15	9.36
Connectedness to peers → investment in learning	−.52***	.20	−2.56
Connectedness to teachers → investment in learning	.01	.05	.30

Note: ***p < .001, **p < .01, *p < .05.

To explore the possibility of clustering effects, the intraclass correlation coefficients (ICCs) were calculated between school and connectedness dimensions as well as domains of self-efficacy. This procedure involved testing a baseline unconditional multilevel model via full information likelihood estimation approach (Raudenbush & Bryk, 2002). This computed between-school variances in connectedness dimensions (i.e. parents, teachers, peers, and school) and academic self-efficacy (i.e. study skills, time management, critical and creative thinking, and investment in learning) domains. Results indicate that ICC values ranged from .01 to .03, suggesting that around 1 to 3% of the variances in school connectedness and academic self-efficacy were accounted for by school-level effects. Consistent with previous research guidelines (Aguinis et al., 2013), hierarchical linear or multilevel modeling was not needed as ICC values are close to zero.

Given that latent constructs with too many observed indicators are likely to result in models with poor fit and biased parameter estimates (Matsunaga, 2008), parceling was used which involved randomly assigning items to a specific parcel indicator. Specifically, 2 parcels for meaning in life and 3 parcels for each dimension of connectedness and academic self-efficacy were created. In total, 26 parcels were used in the subsequent structural equation model.

Structural equation modeling (SEM) via maximum likelihood estimation approach using Analysis of Moment Structure (AMOS) v25 was used to examine the associations among meaning in life, connectedness, and academic self-efficacy. In particular, the final structural model tested the indirect associations of meaning in life to all domains of self-efficacy through the mediating roles of connectedness dimensions (Figure 2

Figure 2.

Structural equation model showing associations among meaning in life, connectedness, and academic self-efficacy. Note: ***p < .001, **p <.01, *p < .05.

). Error terms of all dimensions of connectedness and academic self-efficacy were also correlated. Consistent with Lance et al. (2006) recommended fit for measurement and structural model (i.e. Comparative Fit Index or CFI and Tucker Lewis Index or TLI higher than .90 and Standardized Root Mean Square Residual or SRMR and Root Mean Square Error of Approximation or RMSEA lower than .08), the hypothesized model yielded acceptable fit: χ² = 4929.53, df = 267, p <. 001, CFI = .92, TLI = .90, SRMR = .026, and RMSEA = .063 (.062, .065).

Corroborating Hypothesis 1, meaning in life positively predicted connectedness to parents B = .21, S.E. = .01, p < .001, connectedness to peers B = .21, S.E. = .01, p < .001, connectedness to teachers B = .40, S.E. = .02, p < .001, and connectedness to school B = .52, S.E. = .02, p < .001. These results suggest that meaning in life is linked to increased levels of connectedness to parents, peers, teachers, and schools (Table 2).

Hypothesis 2 was not fully supported as it was only connectedness to school that positively predicted study skills B = 2.97, S.E. = .28, p < .001, time management B = 3.78, S.E. = .35, p < .001, critical thinking B = 2.89, S.E. = .27, p < .001, and investment in learning B = 1.44, S.E. = .15, p < .001. These findings indicate that students’ perceived sense of belonging to school may be associated with better confidence in performing academic tasks. However, connectedness to parents negatively predicted study skills B = −.54, S.E. = .13, p < .001, time management B = −.52, S.E. = .16, p < .001, critical thinking B = −.50, S.E. = .13, p < .001, and investment in learning B = −.22, S.E. = .07, p < .001. Similarly, connectedness to peers negatively predicted study skills B = −2.39, S.E. = .38, p < .001, time management B = −3.19, S.E. = .48, p < .001, critical thinking B = −2.21, S.E. = .37, p < .001, and investment in learning B = −.51, S.E. = .20, p < .01. Connectedness to teachers also negatively predicted study skills B = −.44, S.E. = .08, p < .001, time management B = −.85, S.E. = .10, p < .001, and critical thinking B = −.51, S.E. = .08, p < .001. These findings suggest that perceptions of being connected to parents, teachers, and peers are linked to lower levels of confidence in carrying out academic activities. Path coefficients for these hypothesized paths are reported on Table 2.

Results of bias-corrected bootstrapping analyses showed that connectedness dimensions significantly mediated the link between meaning in life and academic self-efficacy domains, thus confirming Hypothesis 3. In other words, connectedness might serve as a mechanism that accounted for the positive influence of meaning in life on academic self-efficacy. Table 3 reports parameter estimates, confidence intervals, and significance values of indirect effects.¹

Table 3.

Results of indirect effects of meaning in life on academic self-efficacy dimensions via connectedness.

	Study skills		Time management		Critical and creative thinking		Involvement in learning
Mediators	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI
Connectedness to parents, peers, teachers, and school	.745***	.538, .817	.849***	.771, .932	.728***	.662, .797	.598***	.538, .659

***p < .01.

Study 2: Meaning in life, connectedness, and personal self-Efficacy

The objective of Study 2 was to determine any link between meaning in life and domains of connectedness and personal self-efficacy. Indirect effects of meaning in life on personal self-efficacy domains were investigated through the intermediate variable connectedness to parents, school, peers, and teachers. The following hypotheses were tested in Study 2:

Hypothesis 4: Meaning in life would be positively associated with all dimensions of connectedness.

Hypothesis 5: Connectedness dimensions would be positively related to domains of personal self-efficacy.

Hypothesis 6: Meaning in life would have indirect effects on personal self-efficacy dimensions via the mediating role of connectedness dimensions.

Method

In the same way as Study 1, the first author filed an application to the Human Research Ethics Committee of the university to collect data among secondary school students. After approval was granted, the research team contacted the secondary schools. Consent forms were distributed to the participants, and the survey was administered to 4337 students, with a response rate of 92%.

Participants and procedures

Study 2 involved 4,337 Hong Kong secondary school students (ages range: 10 to 18 (M = 13.97, SD = 1.32); 2,158 boys: 2,144 girls [35 students failed to indicate gender]). The students came from school years Grade 7 to Grade 9. Most (76.40%) were born in Hong Kong. Data collected on the educational level of participants’ fathers and mothers revealed that 13.40% and 14% respectively had only primary education or no education, 20.50% and 19.90% respectively had middle school education, 38% and 42.20% had high school education; and 22.60% and 19% respectively had some college education. There were 5.6% and 5.0% missing responses on paternal and maternal educational attainments.

Measures

Meaning in life

The items in the ‘presence of meaning’ dimension within the Meaning in Life Scale (Steger et al., 2006) were used to measure perceived meaning in life. Result of CFA showed that this scale had a good fit: χ² = 79.22, df = 5, p <. 001, CFI = .99, TLI = .99, SRMR = .039, and RMSEA = .059 (.048, .07). All items significantly loaded on higher order meaning latent construct at p < .001. Cronbach’s alpha reliability coefficient for the scale was .82.

Connectedness

The Chinese version of the Hemingway Measure of Adolescent Connectedness – Short Form (Yuen et al., 2010) was used. CFA with a four-factor model of connectedness indicates that the model had poor fit: χ² = 6874.98, df = 246, p <. 001, CFI = .84, TLI = .82, SRMR = .064, and RMSEA = .079 (.077, .080). Revising original measurement model based on modification indices resulted in better fit: χ² = 3631.83, df = 229, p <. 001, CFI = .92, TLI = .90, SRMR = .051, and RMSEA = .059 (.057, .060). Cronbach’s alpha coefficients of the connectedness dimensions were: α_parents = .78, α _school = .74, α_peers = .69, and α_teachers = .74.

Personal self-efficacy

The 24 items in the ‘personal self-efficacy’ subscale of the Life Skills Development Inventories (Yuen et al., 2006) were used to measure the domains of personal self-efficacy (e.g., positive self-concept “Know my own capability”; problem-solving “Generate lots of ways to solve one problem”; self-management “Maintain exercise habit”: and self-reflection “Plan the ways to achieve my goals step by step”). Items were rated on a 6-point Likert-type scale (1 = extremely lacking in confidence; 6 = extremely confident). CFA with a four-factor model of connectedness indicates that the model had poor fit: χ² = 9952.48, df = 246, p <. 001, CFI = .87, TLI = .85, SRMR = .065, and RMSEA = .095 (.094, .097). Modifying original measurement model based on modification indices resulted in better fit: χ² = 5284.12, df = 229, p <. 001, CFI = .93, TLI = .92, SRMR = .054, and RMSEA = .072 (.070, .073). Cronbach’s alpha reliability coefficients of the personal self-efficacy domains were: α_{positive self-concept} = .92, α _{problem-solving} = .88, α_{self-management} = .79, and α_{self-reflection} = .87.

Results and discussion

Preliminary analyses showed that no more than 0.7% of each response per item was missing and results of Little’s MCAR test suggested that these responses were not missing completely at random which enabled us to use expectation maximization imputation approach.

The results of correlation analyses revealed that POM was positively correlated with all domains of school connectedness and personal self-efficacy. School connectedness domains were also linked to higher personal self-efficacy dimensions. The results of descriptive statistical, reliability, and correlation analyses are shown in Table 4.

Table 4.

Descriptive statistics and correlational coefficients among the variables in Study 2.

Variable	r									α	M	SD
	1	2	3	4	5	6	7	8	9
1. Meaning in life	–									.82	23.19	5.79
2. Connectedness to parents	.34**	–								.78	3.49	.66
3. Connectedness to school	.41**	.50**	–							.74	3.40	.61
4. Connectedness to peers	.28**	.39**	.59**	–						.69	3.50	.59
5. Connectedness to teachers	.31**	.44**	.66**	.45**	–					.74	3.43	.63
6. Positive self-concept	.59**	.38**	.49**	.34**	.34**	–				.92	4.32	.99
7. Problem solving	.50**	.36**	.47**	.33**	.34**	.85**	–			.88	4.34	.90
8. Self-management	.44**	.40**	.46**	.34**	.32**	.74**	.77**	–		.79	4.31	.87
9. Self-reflection	.57**	.40**	.51**	.34**	.39**	.84**	.85**	.78**	–	.87	4.36	.89

Note: ** p< .001.

Table 5.

Unstandardized regression weights of the regression analyses in Study 2.

Paths	B	SE	t
Meaning in Life predicting mediators
Meaning in life → connectedness to parents	.25***	.01	17.61
Meaning in life → connectedness to school	.52***	.01	23.45
Meaning in life → connectedness to peers	.21***	.01	15.02
Meaning in life → connectedness to teachers	.42***	.02	17.80
Mediators predicting outcomes
Connectedness to parents → positive self-concept	−.68**	.23	−2.99
Connectedness to school → positive self-concept	6.19***	.66	9.37
Connectedness to peers → positive self-concept	−6.87***	.96	−7.17
Connectedness to teachers → positive self-concept	−1.20***	.18	−6.80
Connectedness to parents → problem solving	−.48**	.19	−2.58
Connectedness to school → problem solving	5.02***	.54	9.24
Connectedness to peers → problem solving	−5.40***	.79	−6.86
Connectedness to teachers → problem solving	−.94***	.15	−6.45
Connectedness to parents → self-management	−.02	.13	−.18
Connectedness to school → self-management	3.55***	.39	9.03
Connectedness to peers → self-management	−3.49***	.56	−6.20
Connectedness to teachers → self-management	−.84***	.11	−7.91
Connectedness to parents → self-reflection	−.50**	.19	−3.05
Connectedness to school → self-reflection	5.02***	.54	9.24
Connectedness to peers → self-reflection	−5.93***	.82	−7.27
Connectedness to teachers → self-reflection	−.87	.15	−5.81

Note: *** p < .001, **p < .01, *p < .05.

Table 6.

Results of indirect effects of meaning in life on personal self-efficacy dimensions via connectedness domains.

	Positive self-concept		Problem-solving		Self-management		Self-reflection
Mediators	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI	Indirect effects	BCa 95% CI
Connectedness to parents, school, peers, and teachers	1.09***	1.00, 1.18	.95***	.88, 1.04	.75***	.69, .83	.95***	.88, 1.04

***p <.01.

In order to assess the likelihood of clustering effects on school connectedness and personal self-efficacy dimensions (positive self-concept, problem-solving, self-management, and self-reflection), ICCs were calculated by testing a baseline unconditional multilevel model (Raudenbush & Bryk, 2002) via full information likelihood estimation approach. ICC values ranged from .018 to .04, which indicates that about 1.8 to 4.0% of the variances in connectedness to parents, teachers, peers, and schools as well as personal self-efficacy dimensions occurred across schools. Corroborating prior research guidelines (Aguinis et al., 2013), it may not be necessary to conduct multilevel modeling.

To assess the indirect effects of meaning in life on personal self-efficacy dimensions via the mediating role of connectedness to parents, peers, teachers, and schools, SEM was conducted via maximum likelihood estimation approach using AMOS (Figure 3). Result demonstrated that the model had good fit: χ² = 4435.84, df = 267, p <. 001, CFI = .94, TLI = .903 SRMR = .027, and RMSEA = .06 (.058, .062).

Corroborating Hypothesis 4, meaning in life positively predicted connectedness to parents B = .25, S.E. = .01, p < .001, connectedness to peers B = .21, S.E. = .01, p < .001, connectedness to teachers B = .42, S.E. = .02, p < .001, and connectedness to school B = .52, S.E. = .02, p < .001. These results suggest that meaning in life is linked to increased levels of connectedness to parents, peers, teachers, and schools (Table 5).

Hypothesis 5 was partially confirmed as it was only connectedness to school that positively predicted positive self-concept B = 6.19, S.E. = .66, p < .001, problem solving B = 5.02, S.E. = .54, p < .001, self-management B = 3.55, S.E. = .39, p < .001, and self-reflection B = 5.02, S.E. = .54, p < .001. These findings indicate that students’ perceived sense of belonging to school may be associated with better confidence in adopting life skills. However, connectedness to parents negatively predicted positive self-concept B = −.68, S.E. = .23, p < .001, problem solving B = −.48, S.E. = .19, p < .001, and self-reflection B = −.50, S.E. = .19, p < .001. Similarly, connectedness to peers negatively predicted positive self-concept B = −6.87, S.E. = .96, p < .001, problem solving B = −5.40, S.E. = .79, p < .001, self-management B = −3.49, S.E. = .56, p < .001, and self-reflection B = −5.93, S.E. = .82, p < .001. Connectedness to teachers also negatively predicted positive self-concept B = −1.20, S.E. = .18, p < .001, problem solving B = −.94, S.E. = .15, p < .001, self-management B = −.84, S.E. = .11, p < .001. Path coefficients of all hypothesized paths are reported in Table 5. These findings suggest that perceptions of being connected to parents, teachers, and peers are linked to lower levels of confidence in carrying out academic activities.

Results of bias-corrected bootstrapping analyses showed that connectedness dimensions significantly mediated the link between meaning in life and academic self-efficacy domains, thus confirming Hypothesis 6. This indicates that connectedness might serve as a concrete psychological process accounting for the positive association of meaning in life on academic self-efficacy. Table 6 reports parameter estimates, confidence intervals, and significance values of indirect effects.²

Conclusions

This research has made three contributions to the existing literature on the concept of meaning in life by demonstrating that meaning in life may be linked to both self-efficacy and connectedness. First, evidence was found that, meaning in life positively predicts academic self-efficacy and personal self-efficacy in school-age students. Second, connectedness to parents, peers, teachers and school appeared to have a positive influence on meaning in life. Third, connectedness served as an important mechanism which could elucidate a positive link between meaning in life and key psychological outcomes in the academic context.

Previous studies have shown that meaning in life is related to higher generalized self-efficacy (Jafary et al., 2011; Lightsey et al., 2014); but the results here suggest that meaning in life can also promote self-efficacy in specific domains of functioning such as academic and personal. It is posited that a reciprocal relationship may exist, through which meaning in life helps students see a purpose for working hard and succeeding in academic studies, and to feel competent at a personal level. At the same time, these feelings of competence and success strengthen a student’s meaning in life.

Converging evidence was obtained regarding the indirect effects of meaning in life on academic and personal self-efficacy via the mediating variable connectedness. The results reported here demonstrate that students reporting high presence of meaning in their life also had stronger perception of connectedness to parents, peers, teachers, and school. These findings corroborate existing data on a positive association of meaning in life with connectedness (Stavrova & Luhmann, 2016; Yuen & Yau, 2015). Psychological constructs that are intrapersonal in nature, like meaning in life, may foster students’ harmonious relations with significant others and school in general (Tice & Baumeister, 2001). These findings suggest sense of connectedness accrued through meaning in life can promote personal and academic self-efficacy. Generally, the findings suggest that different social and contextual factors served as important mechanisms why meaning in life matters for academic and personal self-efficacy. Educators need to help secondary school students cultivate their personal beliefs concerning meaning in life.

However, results of SEM in both Study 1 and Study 2 showed that connectedness to peers, parents, and teachers were linked to lower levels of academic self-efficacy and personal self-efficacy dimensions, even though findings of Pearson-r correlational analyses demonstrated positive directions of correlations. These findings seem to indicate ‘negative statistical suppression, a condition in which addition of predictor variables in a model causes a change in the sign of other predictors (Gutierrez & Cribbie, 2019; Pandey & Elliott, 2010). Thus, future research is needed to understand the role of suppressing variables on the complex nature associations among meaning in life, connectedness dimensions, and self-efficacy beliefs.

Limitations

The study has several limitations. First, the research relied on correlation among the variables, so it is not possible to attribute causal connections from the results. This issue can be addressed in future investigations by carrying out experimental and longitudinal studies to investigate the causal relationships among meaning in life, connectedness and self-efficacy. Second, self-report was used for data collection, which may be prone to social desirability bias in the responses. Future research should, where possible, utilize other approaches for collecting data (e.g., observations of competence in completing academic tasks and objective measures of positive psychological functioning). Third, the student samples were recruited only from Hong Kong so the results may not generalize to other cultural settings. Future research could address this limitation by selecting samples in different socio-cultural contexts (e.g., Australia, South Korea, Singapore and Japan).

Implications for school psychology practice

In the context of the Coronavirus 2019 (COVID-19) pandemic and our “new normal” world, adolescents need to cope with transitions in academic learning while maintaining mental wellbeing (Prothero, 2020). School psychologists could collaborate with educators in developing and implementing face-to-face and online programs that promote students’ reflection upon meaning and purpose in life, connectedness, academic and personal self-efficacy (Koh, 2020; Reber, 2019; Steger, 2020; Yuen, 2011; Yuen et al., 2015). School-based life skills development and mentoring programs could reduce loneliness and enhance meaning in life, connectedness and psychological well-being of adolescents (Karcher, 2005; To, 2016; Yuen et al., 2020)

Figure 3.

Structural equation model showing associations among meaning in life, connectedness, and personal self-efficacy. Note: *** p < .001, **p < .01, *p < .05.

Footnotes

Acknowledgements

The first author and second author share equal contributions to the paper. We are grateful to Norman Gysbers, Patrick SY Lau, Raymond M C Chan, Peter MK Shea, Sherin Ke, Ida Yip, Virginia Cheung, Ryder Chan and Peter Westwood for their input to the project. The project would not have been completed without the generous support of teachers, guidance personnel and students in the participating schools. Their valuable contribution to the research is greatly appreciated.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The preparation of this paper was partly funded by the Hong Kong Research Grant Council (HKU 756312).

Notes

1. In Study 1, an alternative structural model was tested which involved reversed pattern of associations among meaning in life, connectedness, and academic self-efficacy dimensions (i.e. academic self-efficacy -> connectedness dimensions -> meaning in life). Result showed that this model had χ² = 4929.53, df = 267, p <. 001, CFI = .92, TLI = .90, SRMR = .026, and RMSEA = .063 (.062, .065). As this model did not significantly differ from originally hypothesized structural model, the latter was adopted as final model for Study 1.

2. Study 2 also evaluated fit of an alternative model with reversed pattern of relationships among meaning in life, connectedness, and personal self-efficacy dimensions (i.e. personal self-efficacy -> connectedness dimensions -> meaning in life). Result showed that this model had χ² = 4435.84, df = 267, p <. 001, CFI = .94, TLI = .93, SRMR = .027, and RMSEA = .06 (.058, .062). Given that this model did not differ from the originally hypothesized structural model, the latter was used as final structural model for Study 2.

ORCID iDs

Mantak Yuen

Jesus Alfonso D. Datu

Author biographies

Mantak Yuen is an Associate Professor and Director of the Laboratory for Creativity and Talent Development, Centre for Advancement in Inclusive and Special Education, Faculty of Education, University of Hong Kong. He has expertise in career counseling and talent development, with a particular interest in giftedness and emotional well-being.

Jesus Alfonso D. Datu is an Assistant Professor in the Department of Special Education and Counselling at The Education University of Hong Kong (EdUHK). He is also an Affiliated Researcher of Integrated Centre for Wellbeing. He is a well-being scientist with expertise in positive psychology and positive education.

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